System and device for preliminary diagnosis of ocular diseases

ABSTRACT

A system for preliminary diagnosis of ocular diseases is proposed, in which from capturing a plurality of images of the eyes of a person, a final image, corrected by processing the images by a computer application, is obtained. The already mentioned application calculates the percentage of the colors composing the pupillary reflex of each eye, and compares the results with previous reference pictures obtained from normal cases and clinical cases of ocular diseases.

GOVERNMENT SUPPORT

This invention was made with U.S. Government support under Grant No.PGRD 16-0004-005 awarded by the United States Agency for InternationalDevelopment (“USAID”). The U.S. Government has certain rights in theinvention.

BACKGROUND

1. Field of the Invention

The present invention relates to the field of ophthalmology, andparticularly provides a system and a configured device for preliminarydiagnosis of ocular diseases, which is based on imaging of the eyes andon the diagnosis of ocular disorders, on the basis of the processing ofthese images and the reflection values of the retina and/or the pupilthat they provide.

2. Description of Related Art

An estimate based on the National Health Survey (ENS 2007) indicatesthat at least 1.5% to 2.6% of the Chilean population has some visualimpairment, of this percentage is estimated that at least ¼ of them haschronic defects classified as blindness. The world situation is not sodifferent, and this reveals that there are at least 12 million childrenunder the age of 10, which is the age group of preventive control,suffer from visual impairment due to refractive error (myopia,strabismus or astigmatism) in addition there are more severe cases likeocular cancer that affects 1 in 12,000 live births, which is usuallyseen in children up to 5 years old. All of these conditions and others,in most cases can be corrected without major complications with apreventive diagnosis and effective treatment in infants from birth toabout 5 years old, preventing these disorders getting worse with timeand treatment being too expensive, ineffective or simply being too lateto be implemented.

Most of these problems could be detected at an early age, but requirecontinuous medical supervision and examinations which are carried outwith high-cost instruments that also require the presence of specialiststo use them.

For the group of infants (0-5 years) which is the control group andprimary diagnosis, there are two key problems in performing these tests:it is difficult to make that infants focus their gaze intently to anydevice that performs the test and also the ophthalmologist orpediatrician has only fraction of a second to capture the image beforethe pupil shrinks in response to the bright flash light. These problemslead to pediatricians are unable to detect ocular problems early, andtherefore cannot effectively take preventive measures before the problemgetting worse.

The red pupillary reflex is fairly well understood by ophthalmologistsand pediatric specialists worldwide, and has been used as a diagnosticinstrument around the world since the 60s. Normally, the light reachesthe retina and a portion of it is reflected off the pupil by the choroidor posterior uvea, which is a layer of small vessels and pigmented cellslocated near the retina. The reflected light, seen from a coaxialinstrument to the optical plane of the eye, normally present a reddishcolor, due to the color of blood and pigments of the cells, so thiscolor can vary from shiny reddish or yellowish in people with lightpigmentation to a more grayish red or dark pigmentation in people withdark pigmentation. In 1962, Bruckner (Bruckner R. Exakte Strabismusdiagnostic bei 1/2-3 jahrigen Kindern mit einem einfachen Verfahren, dem“Durchleuchtungstest.” Ophthalmologica 1962; 144: 184-98) describedabnormalities in the pupillary reflex as well as in quality, intensity,symmetry or presence of abnormal figures, therefore, pupilar red colortest is also known as Bruckner test. Another similar test is theHirschberg test, which uses the corneal reflex to detect misalignment ofthe eyes, which enables to diagnose some degree of strabismus (Wheeler,M. “Objective Strabismometry in Young Children.” Trans Am Ophthalmol Soc1942; 40: 547-564). In summary, these tests are used to detectmisalignment of the eyes (strabismus), different sizes of the eyes(anisometropy), abnormal growths in the eye (tumors), opacity (cataract)and any abnormalities in the light refraction (myopia, hyperopia,astigmatism).

The evaluation of the pupillary and corneal reflexes is a medicalprocedure that can be performed with an ophthalmoscope, an instrumentinvented by Francis A. Welch and William Noah Allyn in 1915 and usedsince the last century. Today, his company Welch Allyn, has productsthat follow this line as Pan Optic™. There are also photographicscreening type portable devices for the evaluation of pupilar red coloras Plusoptix (Patent application No. WO9966829) or Spot™ Photoscreener(Patent Application No. EP2676441A2), but the cost ranges between USD100 to 500, they weigh about 1 kg and also require experience ininterpreting the observed images.

With regard to state of the art, concerning computer applications forthe prompt diagnosis of ocular diseases, the application No. FR2876570A1 by Mawas, presents a process to obtain a picture with a camera andremit it in negative to a specialist ophthalmologist via email, in orderto detect strabismus (Hirschberg test); however, this lacks theprocessing of the image, the immediately preliminary diagnosis and itsapplication to mobile devices. The patent application No. US2013235346A1 by Huang, points to a smart device application to obtain a set ofpictures, at two specified working distances, and four orientations torun of photo-refraction tests, Bruckner and Hirschberg test, butrequires masks that function like outlines on the screen, where thepatient's face is fixed to obtain working distances, and there is nosubsequent processing of images for a higher quality image.

The present invention is a practical and reliable solution for rapiddiagnosis of ocular problems, which allows a preliminary examinationonly with the use of smart phones or tablet type devices, currently usedby millions of people worldwide. The application can be run by parents,paramedics, pediatricians and ophthalmologists without the need for amore complex instrument or experience in the use of these, andeffectively allows conducting a test to detect ocular problems. Thisapplication prototype was tested in 100 infants, from which 3 childrenwith problems were detected, and which were referred to specialists whopositively found ocular problems. The system allows to conduct apreliminary medical test regarding to the pupillary reflex (pupillaryred color test or Bruckner test) and corneal reflex (Hirschberg test).

SUMMARY OF THE INVENTION

The present invention relates to a system for the preliminary diagnosisof ocular diseases, said system comprising:

-   -   a device for capturing images or a camera;    -   a device generating light or a flash;    -   a screen for displaying the image;    -   a memory for storing data    -   a computational application stored in the memory that executes        the process of capturing a plurality of images of the eyes of an        individual, and a final corrected image obtained through the        processing of said plurality of images, by performing a        post-processing of the final image corrected by calculating the        percentage of the colors that compose the pupillary reflex of        each eye and comparing it with the values obtained for previous        clinical cases;    -   and a processor functionally attached to the camera, the flash,        the screen and the memory, such that runs the application.

In the system of the invention, the memory further includes images forthe comparison of the final corrected image with previously diagnosedclinical cases, with ocular diseases.

The system can be implemented by using a computational device, a smartphone, or any device with connection to a camera, either an internalcamera or a webcam and a system of a lighting device, of a built-inflash type.

The present invention also includes an “ex vivo” method for thepreliminary diagnosis of ocular diseases, comprising the steps of:

-   -   focusing the image of the individual's eyes, using a camera and        a screen of a computing device;    -   eliminating ambient lighting; in case a light is on in the room,        the light is turned off, and if there is natural light, closing        the windows or curtains to decrease it;    -   capturing a plurality of images of the individual's eyes with        said camera, using the flash;    -   processing the plurality of images, by using a computational        application in order to obtain a final corrected image of the        individual's eyes;    -   displaying the said final corrected image on the screen and        visually comparing it with clinical cases previously diagnosed        with ocular diseases.

For the processing of the plurality of images, in order to obtain afinal corrected image, the computational application includes thefollowing steps:

-   -   i. making a first selection of images from the plurality of        images;    -   ii. obtaining an approximation of the area of the individual's        face in each image of the said first selection;    -   iii. aligning the mentioned first selection of images, from the        edge detection by its spatial translation in each image of the        said first selection;    -   iv. determining the area of the two eyes in each image of the        said first selection;    -   v. obtaining a determined location of the center of the two eyes        from each image of the said first selection;    -   vi. making a second selection of images, from said first        selection, to select a single image of the individual's eyes        with greater sharpness;    -   vii. processing that said single image to obtain a final        corrected image with greater focus;    -   viii. cutting the eyes of the individual from that final        corrected image, from the determined location of the centers and        calculating the area of the two eyes; and    -   ix. post-processing the final corrected image, to detect the        percentage of the colors that compose the pupillary reflex.

The computational application makes the said first selection from theplurality of images obtained by the camera, discriminating on theluminance of the pixels and selecting in said first selection between 1and 60 images, preferably, between the best 10 images.

The computational application obtains the approximation of theindividual's face, detecting it in a first image captured from the saidfirst selection, and then cutting the area of all the later images tothe first image for further processing.

On the other hand, for aligning the said first selection of theplurality of images, the computational application finds the edges inthe first image captured from said first selection, and searches theseedges in the later images, to calculate the translation of these imageswith respect to said first image. Then, it calculates the location ofthe centers of the pupil of each eye for each image, removing outliersand averaging the position of said centers obtained to get the bestdetermined location of the centers.

The computational application makes a second selection with respect tothe sharpness of each image of said first selection, obtaining a valuewhich is representative of the sharpness of each image and selecting theone image with greater sharpness, which is corrected in order to obtainthe final corrected image with greater focus, using the area of each eyeand the determined location of the centers.

Finally, the computational application performing a post-processing ofthe final corrected image, by calculating the percentage of the colorsthat compose the pupillary reflex of each eye, selecting the red, white,orange and yellow colors.

In this process, the following three cases are defined:

-   -   If the red color is in a range greater than 50% of the pixels        that compose the area of the pupil, in any of the eyes of the        final processed image, the image is considered most likely of a        normal eye.    -   If the red color is in a range greater than 50% of the pixels        that compose the area of the pupil, while the yellow and/or        orange percentages correspond to a higher range of 10% of the        pixels that compose the area of the in one of the eyes of the        final processed image, the eye probably presents a type of        refractive defect.    -   If the red color is in a range lower than 50% of the pixels that        compose the area of the iris and the pupil, while white        corresponds to a percentage higher than 40% in any of the eyes        of the final processed image the diagnosis corresponds to a        suspicion for organic and/or structural disease.

Clinical cases that are previously diagnosed and used as reference forcomparison of the images that the system of invention produce, consistof a set of three or more images previously obtained by the computingdevice, which represent normal cases, clinical cases of refractivedefects and other ocular diseases.

Within the cases of refractive defects of the group that can bediagnosed with the system of the invention, we can found hyperopia,astigmatism and myopia; and it is also possible to make a fast screeningof other ocular diseases, such as organic diseases and ocular functionaldiseases, Including tumors, malformations, strabismus, cataracts, etc.

DESCRIPTION OF THE DRAWINGS

The novel features believed characteristic of the application are setforth in the appended claims. However, the application itself, as wellas a preferred mode of use, and further objectives and advantagesthereof, will best be understood by reference to the following detaileddescription when read in conjunction with the accompanying drawings,wherein:

FIG. 1 is a front and rear view of a smart phone, according to theinvention.

FIG. 2 is an example of using the device while the individual's eyes arefocused, in this case, infant eyes.

FIG. 3 is a screenshot of the application, running on a device accordingto the invention.

FIG. 4 is an example of a diagnosis type, obtained from the device,according to the invention, of the normal pupillary reflex.

FIG. 5 is an example of a diagnosis type, of a pupillary reflex withrefractive ocular problems.

FIG. 6 is an example of a diagnosis type, of a pupillary reflex withserious ocular problems.

FIGS. 7A and 7B are a comparison of an image obtained by an electronicdevice according to the invention (FIG. 7A), compared to the final imageprocessed by the application in the same computing device (FIG. 7B).

While the system and method of the present application is susceptible tovarious modifications and alternative forms, specific embodimentsthereof have been shown by way of example in the drawings and are hereindescribed in detail. It should be understood, however, that thedescription herein of specific embodiments is not intended to limit theapplication to the particular embodiment disclosed, but on the contrary,the intention is to cover all modifications, equivalents, andalternatives falling within the spirit and scope of the process of thepresent application as defined by the appended claims.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Illustrative embodiments of the preferred embodiment are describedbelow. In the interest of clarity, not all features of an actualimplementation are described in this specification. It will of course beappreciated that in the development of any such actual embodiment,numerous implementation-specific decisions must be made to achieve thedeveloper's specific goals, such as compliance with system-related andbusiness-related constraints, which will vary from one implementation toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming but would nevertheless be a routineundertaking for those of ordinary skill in the art having the benefit ofthis disclosure.

In the specification, reference may be made to the spatial relationshipsbetween various components and to the spatial orientation of variousaspects of components as the devices are depicted in the attacheddrawings. However, as will be recognized by those skilled in the artafter a complete reading of the present application, the devices,members, apparatuses, etc. described herein may be positioned in anydesired orientation. Thus, the use of terms to describe a spatialrelationship between various components or to describe the spatialorientation of aspects of such components should be understood todescribe a relative relationship between the components or a spatialorientation of aspects of such components, respectively, as the devicedescribed herein may be oriented in any desired direction.

The present invention relates essentially to a system and methodemploying a computational application that can be executed on mobiledevices and related devices, which allows obtaining a preliminaryexamination of ocular conditions, using the pupillary and cornealreflexes obtained from a photograph of the eyes.

Unlike the old cameras of the non-digital age, digital cameras andmobile devices, like current smartphones or tablets, are programmed witha temporary setup between camera and flash, in such a way to avoid thereflection of the red pupil in the pictures that are obtained with them.However, is not well known that this reflex has important informationabout ocular diseases, and can be used for their detection as apreliminary screening using the invention.

Since mobile devices are currently used by millions of people around theworld, the purpose of the present invention is to provide an applicationeasy to use to the general population, without requiring the utilizationof complex ophthalmic instruments, and which recreates the effect of oldcameras that can capture the reddish reflex of the eyes, but alsoincludes a processing of the obtained image, so this reflection to besharper and more focused.

The present invention, therefore, is a useful tool for the early andpreliminary detection of ocular diseases, which are then confirmed byspecialists. Furthermore, this computational application has beenparticularly useful for avoiding problems associated to perform ocularexaminations in infants, since through it is not necessary to sleepthem, keep them focused, or subjected to long ocular examinations, isnot necessary to dilate their pupils by using pharmacological drops,with the consequent disadvantages that they usually produce. The presentinvention can perform this examination by simply lowering the ambientlighting before taking the pictures of the eye, using the flash. Infantsare the group of greatest need for continuous ocular controls, becauseat this age they can develop many of the ocular problems that could haveon their lives as adults, which often fail to be detected early.

The computational application of the present invention can be installedin any electronic device. A non-limiting example of a smartphone,according to the invention, is an iPhone 4S®, marketed by Apple Inc.,and shown in FIG. 1. This smartphone has a camera for capturing images(lens 1), a device generating light or flash 2, a screen 3 that allowsdisplaying images and serves to focus on the individual, a memory thatstores the application and images, and a processor that runs theapplication to obtain the final images.

In FIG. 2, is represented how the camera of the device in question isactivated, the output of the camera is shown on screen 3. The focuspoint 4 is marked with respect to the individual's eyes 5 by touchingthe screen 3, in order to proceed, subsequently, to lower the amount ofambient lighting. The pupil dilates naturally being in low light, so, atthis moment, the taking of a plurality of images is activated, using theapplication.

FIG. 3, which is a graphical representation of a screenshot of theapplication, shows the button 6 for the initiation of taking a pluralityof images, a setting button 7 and a button 8 to display the imagesobtained.

To begin capturing pictures, the application turns on the flash light 2,but the pictures will begin to be processed when the applicationestimates that what is being captured is already under the influence oflight from the flash. The application estimates the amount of lightcontained in each image, transforming these to Y′UV color space, whichrepresent a luminance component Y′ and two chrominance components UV.The application calculates the average of the component Y′, whichrepresents the luminance of the pixel. Then, calculating the luminancebefore starting and during the frames, the application discriminatesfrom which frame to start capturing, as it is known from this frame,that the flash 2 is affecting the captured image.

Frames containing no flash light 2 are discarded. The applicationperforms it by removing an arbitrary number of frames captured since theflash 2 started to work, so then be able to capture ten images to beused in the process.

The capture of the first image of the process is different from theothers, since in this frame the approximate area of the individual'sface is detected using an appropriate “haar cascade”, which is a processthat captures the best section of the individual's face, and thissection is cropped, obtaining the image to be used; this minimizes theamount of information to be processed by the application. In order toobtain the rest of the images, the same detected area is cropped,obtaining images of the same size as the first. Notably, the firstframes pictures since the flash 2 has an effect, where the greatesteffect on the retina reflex occurs, because at that time the pupil isdilated by the little pre-flash light. For this reason, the number ofused frames does not exceed ten.

By completing the capture of the ten images, a camera stabilizationprocess is performed, which helps to reduce camera shake or movement ofthe person in the sequence. To achieve this, first the position of theprominent edges of the image (“good features to track”) is detected.These same points are then searched in the next image frame bycalculating the “optical flow”. After obtaining the points of the firstimage in the following one, the calculation of the translationalsuffered by the following image, regarding its predecessor, isperformed. For this, the average of the motion vectors of all theprominent edges of this is calculated by transferring the image by thatamount. This allows the eyes to be always in the same position in allthe taken pictures, so it is possible, as will be explained later, toperform the detection of the important features, using not one, butseveral pictures.

With the images already aligned the area enclosed by each eye of each ofthe images is calculated, using a “cascade haar” both for the right eyeand the left eye. Afterwards, using the image gradients the center ofthe pupil of each eye is obtained in each image. After, the images whereall the features could not be detected are discarded.

At this time, a set of positions of centers and a set of areas where theeyes are, are available. With this, it is possible to calculate aposition that represents better the eye center. To do this, first alloutliers from the set of centers are eliminated and then position of allof them are averaged. A similar process is applied to each of thesquares enclosing the eyes, getting the best square enclosing each eye.At the end, the process selects the picture that is less blurry as thefinal image.

To perform the above, a defocusing of each of the images, using aGaussian filter is performed. Then, the fast Fourier transform (FFT) iscalculated, and the average of 90% of the highest values are calculated,obtaining a value that estimates how sharper the image is. The chosenimage is also passed by another process called “unsharp masking” tofocus it digitally, which consists of blurring the image, using aGaussian blur and subtracting the result to the original image on aweighted basis for a larger focus. Then, the portion of the image iscropped in the best frame obtained in the previous step for each eye,and another image, corresponding to the pupil and iris of the eye iscropped, from the best center also obtained in the previous step.

By the process just described, a good reflection on the retina can beobtained, producing a color which allows diagnostic analysis. This coloris usually related to the internal condition of the eye. In a normalpatient, this will be reddish tonality; and in abnormal cases coulddetect a white color that may indicate the existence of some abnormalbody into the eye, or a yellow color indicating some eye deformation. Soa post processing in which it is necessary to detect what color appearedin the pupil reflex shooting takes place. To do this the amount of red,white and yellow color in the image of the pupil is calculated. To dothis the image of the pupil of each eye is transformed to HSV colorspace and passed through a mask that leaves in color white all colorswithin a specific range. The percentage of white pixels is thencalculated, getting the percentage of that color in the image.

-   -   If the predominant color is red, it is likely that the eye looks        normal. FIG. 4 is an example of this case, where the reflection        of the red pupil 10, 11, 12 and 13 seen in both eyes is normal.    -   If the predominant color is red, with a percentage of orange or        yellow color, is likely to have a common problem in sight. FIG.        5 is an example of this case, where the presence of a yellow        reflection in the right eye 14 of the patient may be a sign of        refractive errors or strabismus. It is recommended for this        patient to request a visit to the ophthalmologist.    -   If the predominant color is white, there is probably a problem        with a tumor disease in the eye. FIG. 6 is an example of this        case, where the reflection of the red reflex seen in the right        eye 15 is normal. The white reflection in the left eye 16 may be        a sign of a dangerous condition within the patient's eye. It is        recommended for the patient to visit an ophthalmologist as soon        as possible, urgently.    -   In case none of the above situations occurs, the analysis does        not reach a conclusive result, so the patient should require an        expert and conduct more complex tests with the proper equipment,        to obtain a more accurate diagnosis.

Finally, the final processed image (FIG. 7B) can be seen, to be used fordiagnosing ocular diseases. FIGS. 7A and 7B show a comparison between anormally captured image with an electronic device, according to theinvention (FIG. 7A) and the final image processed by the computerapplication (FIG. 7B).

The particular embodiments and steps disclosed above are illustrativeonly, as the application may be modified and practiced in different butequivalent manners apparent to those skilled in the art having thebenefit of the teachings herein. It is therefore evident that theparticular embodiments and steps disclosed above may be altered ormodified, and all such variations are considered within the scope andspirit of the application. Accordingly, the protection sought herein isas set forth in the description. It is apparent that an application withsignificant advantages has been described and illustrated. Although thepresent application is shown in a limited number of forms, it is notlimited to just these forms, but is amenable to various changes andmodifications without departing from the spirit thereof.

What is claimed is:
 1. A system for the preliminary diagnosis of oculardiseases, the system comprising: a camera; a flash; a screen fordisplaying at least one image; a memory for storing data and acomputational application; and a processor coupled to the camera, theflash, the screen and the memory, wherein upon execution of thecomputational application by the processor, the processor: controls thecamera and the flash to capture a plurality of images of the eyes of anindividual, wherein the plurality of images have a same orientation; andprocesses said plurality of images to obtain a final corrected image by:estimating an amount of light contained in each image of the pluralityof images; discarding one or more respective images that contain noflash light, based on the estimated amount of light contained in eachimage of the plurality of images, thereby obtaining a plurality ofremaining images; detecting, in a first image of the plurality ofremaining images, an approximate area of the face of the individualusing an appropriate haar cascade; cropping said approximate area fromsaid plurality of remaining images, thereby obtaining a plurality ofcropped images; performing a camera stabilization process on saidplurality of cropped images, thereby obtaining a plurality of stabilizedcropped images; obtaining an average position of the center of the pupilof each eye of the individual and an average area enclosing each eye ofthe individual from said plurality of stabilized cropped images; andselecting one stabilized cropped image of the plurality of stabilizedcropped images that has the greatest sharpness as the final correctedimage.
 2. The system of claim 1, wherein: the memory further storesimages of previously diagnosed clinical cases with ocular diseases; andupon execution of the computational application by the processor, theprocessor: calculates, in the final corrected image, percentages ofrespective colors that compose the pupillary reflex of each eye; andcompares the calculated percentages of the respective colors with valuesobtained from the images of previously diagnosed clinical cases.
 3. Thesystem of claim 1, wherein the system comprises a smart phone thatincludes the camera.
 4. The system of claim 3, wherein the smart phonefurther includes the flash.
 5. A method for the preliminary diagnosis ofocular diseases, the method comprising: capturing a plurality of imagesof the eyes of an individual with a camera using a flash, wherein theplurality of images have a same orientation; processing the plurality ofimages, to obtain a final corrected image of the eyes of the individual;and displaying said final corrected image on a display screen; whereinprocessing the plurality of images comprises: estimating an amount oflight contained in each image of the plurality of images; discarding oneor more respective images that contain no flash light, based on theestimated amount of light contained in each image of the plurality ofimages, thereby obtaining a plurality of remaining images; detecting, ina first image of the plurality of remaining images, an approximate areaof the face of the individual using an appropriate haar cascade;cropping said approximate area from said plurality of remaining images,thereby obtaining a plurality of cropped images; performing a camerastabilization process on said plurality of cropped images therebyobtaining a plurality of stabilized cropped images; obtaining an averageposition of the center of the pupil of each eve of the individual and anaverage area enclosing each eye of the individual from said plurality ofstabilized cropped images; and selecting one stabilized cropped image ofthe plurality of stabilized cropped images that has the greatestsharpness as the final corrected image.
 6. The method of claim 5,wherein: performing the camera stabilization process on said pluralityof cropped images comprises aligning the plurality of cropped images byedge detection and spatial translation to obtain the plurality ofstabilized cropped images; and obtaining an average position of thecenter of the pupil of each eye of the individual and an average areaenclosing each eye of the individual from said plurality of stabilizedcropped images comprises: determining respective areas enclosing theeyes of the individual in each image of said plurality of stabilizedcropped images; and obtaining respective locations of the centers of theeyes from each image of said plurality of stabilized cropped images. 7.The method of claim 6, wherein aligning the plurality of cropped imagesby edge detection and spatial translation to obtain the plurality ofstabilized cropped images comprises: detecting first edges in a firstimage of the plurality of cropped images; detecting the first edges inat least one subsequent image of the plurality of cropped images; andcalculating a translation of the at least one subsequent image based onthe detected first edges in the at least one subsequent image.
 8. Themethod of claim 5, wherein: estimating an amount of light contained ineach image of the plurality of images comprises calculating a luminanceof pixels in each image; and discarding one or more respective imagesthat contain no flash light comprises discarding the one or morerespective images based on the calculated luminance.
 9. The method ofclaim 5, wherein a number of said plurality of remaining images rangesfrom 10 to 60 images.
 10. The method of claim 5, wherein obtaining saidaverage position of the center of the pupil of each eye of theindividual comprises: calculating the location, in each image of theplurality of stabilized cropped images, of the center of the pupil ofeach eye to obtain a plurality of positions of the center of the pupilof each eye; removing outliers from the plurality of positions to obtaina plurality of remaining positions; and averaging the plurality ofremaining positions to get the average position of the center of thepupil of each eye.
 11. The method of claim 5, wherein selecting onestabilized cropped image of the plurality of stabilized cropped imagesthat has the greatest sharpness as the final corrected image comprises:defocusing each image of the plurality of stabilized cropped imagesusing a Gaussian filter; calculating a Fast Fourier Transform (FFT) foreach defocused image to obtain an image sharpness value that estimatesan image sharpness of each image; and selecting the final correctedimage based at least in part on respective image sharpness values. 12.The method of claim 5, further comprising: calculating, from the finalcorrected image, percentages of respective colors in the pupillaryreflex of each eye, wherein the respective colors include red, white,orange and yellow colors.
 13. The method of claim 12, furthercomprising: determining whether or not the red color is in a rangegreater than 50% of pixels that compose an area of the pupil of each eyein the final processed image.
 14. The method of claim 13, wherein thered color is in a range greater than 50% of the pixels that compose thearea of the pupil, and the method further comprises: determining whetheror not the yellow color and/or the orange color correspond topercentages in a range greater than 10% of the pixels that compose thearea of the pupil of each eye in the final processed image.
 15. Themethod of claim 13, wherein the red color is in a range less than 50% ofthe pixels that compose the area of the iris and the pupil, and themethod further comprises: determining whether or not the white colorcorresponds to a percentage greater than 40% of the pixels that composethe area of the pupil of each eye in the final processed image.
 16. Themethod of claim 5, further comprising: comparing the final processedimage with a plurality of previous images corresponding to previouslydiagnosed clinical cases, wherein the previously diagnosed clinicalcases represent at least one of normal cases, clinical cases ofrefractive defects, and cases of other ocular diseases; and wherein saidrefractive defects are selected from the group consisting of hyperopia,astigmatism and myopia.
 17. The method of claim 16, wherein said otherocular diseases are selected from the group consisting of organicdiseases and functional diseases.
 18. The method of claim 5, furthercomprising: processing said final corrected image to obtain a finalcorrected image with greater focus; cutting the eyes of the individualfrom the final corrected image with greater focus, from the averageposition of the center of the pupil of each eye and said average areaenclosing each eye of the individual; and post-processing the finalcorrected image with greater focus, to determine percentages ofrespective colors that compose the pupillary reflex of each eye in thefinal corrected image with greater focus.
 19. A method for thepreliminary diagnosis of ocular diseases, the method comprising:capturing a plurality of images of the eyes of an individual with acamera using a flash; processing the plurality of images to obtain afinal corrected image of the eyes of the individual; and displaying saidfinal corrected image on a display screen, wherein processing theplurality of images comprises: estimating an amount of light containedin each image of the plurality of images; discarding one or morerespective images of the plurality of images that contain no flashlight, based on the estimated amount of light contained in each image ofthe plurality of images, thereby obtaining a plurality of remainingimages; detecting, in a first image of the plurality of remainingimages, an approximate area of the face of the individual using anappropriate haar cascade; cropping said approximate area from saidplurality of remaining images, thereby obtaining a plurality of croppedimages; performing a camera stabilization process on said plurality ofcropped images, thereby obtaining a plurality of stabilized croppedimages; obtaining an average position of the center of the pupil of eacheye of the individual and an average area enclosing each eye of theindividual from said plurality of stabilized cropped images; andselecting one stabilized cropped image of the plurality of stabilizedcropped images that has the greatest sharpness as the final correctedimage, wherein: estimating an amount of light contained in each image ofthe plurality of images comprises calculating a luminance of pixels ineach image; discarding one or more respective images that contain noflash light comprises discarding the one or more respective images basedon the calculated luminance; a number of said plurality of remainingimages ranges from 10 to 60 images; and the method further comprisescalculating, from the final corrected image, percentages of respectivecolors in the pupillary reflex of each eye, wherein the respectivecolors include red, white, orange and yellow colors.